CC*IIE Networking Infrastructure: A High-Speed Scalable Research Core (HSSRC) at Washington State University
CC*IIE Networking Infrastructure: A High-Speed Scalable Research Core (HSSRC) at Washington State University
批准号:
1440546
负责人:
Tony Opheim
金额:
$49.81万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-10-01 至 2016-09-30
中文摘要
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英文摘要
Washington State University (WSU) is embracing scientific computing in research and education by implementing an overarching strategy to build capacity and capabilities in computational and data science and to better respond to the emerging, diverse, and rapidly evolving needs of the university's research community across several disciplines. To catalyze new multi-disciplinary research applications, accelerate data-driven scientific discovery, and enable transformative training activities, WSU is improving its high-speed network infrastructure by establishing a High Speed Scalable Research Core (HSSRC) to access wide-area science services and software-defined networking environments. The deployment of the HSSRC at WSU advances the state-of-knowledge within the participating scientific disciplines by enabling the data resulting from simulations and instruments to be analyzed more rapidly and efficiently. For example, access to the HSSRC allows materials scientists to apply predictive theory and simulation capabilities to efficiently explore the structure-properties-performance parameter space and design new materials with optimized and tailored properties; enables nuclear theorists to unlock the unsolved mysteries of our cosmos; allows energy grid engineers to analyze in real-time the large number of power grids scenarios; and opens the possibility for researchers in genomics, genetics, and bioinformatics to dissect the genomic basis of diversity and answer questions that range from disentangling the evolutionary history of organisms to linking genomic changes to phenotypic changes. Moreover, the deployment of a HSSRC at WSU enables the training of the next generation of scientific leaders with knowledge and experience in a broad range of modeling and simulation disciplines and "big data" science.
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